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archana-ramalingamarchana-ramalingam
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Remove duplicate tests
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‎test/Conversion/TorchOnnxToTorch/simple_ops_q_to_z.mlir

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Original file line numberDiff line numberDiff line change
@@ -1069,82 +1069,6 @@ func.func @test_reduce_sum_negative_axes_keepdims_example(%arg0: !torch.vtensor<
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// -----
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// CHECK-LABEL: func.func @test_reduce_log_sum_exp_default_axes_keepdims_example
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func.func @test_reduce_log_sum_exp_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK: %[[INT7:.+]] = torch.constant.int 7
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// CHECK: %[[NONE:.+]] = torch.constant.none
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// CHECK: %[[FALSE:.+]] = torch.constant.bool false
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// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[1,1,1],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
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// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[1,1,1],f32> -> !torch.vtensor<[1,1,1],f32>
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// CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct : () -> !torch.list<int>
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// CHECK: %[[TRUE:.+]] = torch.constant.bool true
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// CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
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// CHECK: %[[LOG:.+]] = torch.aten.log1p %[[SUM]] : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
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// CHECK: %[[CASTLIKE:.+]] = torch.aten.to.dtype %[[LOG]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[1,1,1],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,1,1],f32>
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// CHECK: return %[[CASTLIKE]] : !torch.vtensor<[1,1,1],f32>
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%0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32>
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return %0 : !torch.vtensor<[1,1,1],f32>
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}
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// -----
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// CHECK-LABEL: func.func @test_reduce_log_sum_exp_do_not_keepdims_example_expanded
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func.func @test_reduce_log_sum_exp_do_not_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK: %[[INT7:.+]] = torch.constant.int 7
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// CHECK: %[[NONE:.+]] = torch.constant.none
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// CHECK: %[[FALSE:.+]] = torch.constant.bool false
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// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f32>
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// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
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// CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct : () -> !torch.list<int>
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// CHECK: %[[TRUE:.+]] = torch.constant.bool true
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// CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
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// CHECK: %[[LOG:.+]] = torch.aten.log1p %[[SUM]] : !torch.vtensor<[3,2],f32> -> !torch.vtensor<[3,2],f32>
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// CHECK: %[[CASTLIKE:.+]] = torch.aten.to.dtype %[[LOG]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2],f32>
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// CHECK: return %[[CASTLIKE]] : !torch.vtensor<[3,2],f32>
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%0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32>
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return %0 : !torch.vtensor<[3,2],f32>
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}
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// -----
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// CHECK-LABEL: func.func @test_reduce_log_sum_exp_keep_dims_example
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func.func @test_reduce_log_sum_exp_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK: %[[INT7:.+]] = torch.constant.int 7
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// CHECK: %[[NONE:.+]] = torch.constant.none
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// CHECK: %[[FALSE:.+]] = torch.constant.bool false
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// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],f32>
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// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],f32> -> !torch.vtensor<[3,2,2],f32>
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// CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct : () -> !torch.list<int>
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// CHECK: %[[TRUE:.+]] = torch.constant.bool true
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// CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2,1],f32>
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// CHECK: %[[LOG:.+]] = torch.aten.log1p %[[SUM]] : !torch.vtensor<[3,2,1],f32> -> !torch.vtensor<[3,2,1],f32>
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// CHECK: %[[CASTLIKE:.+]] = torch.aten.to.dtype %[[LOG]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,1],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,1],f32>
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// CHECK: return %[[CASTLIKE]] : !torch.vtensor<[3,2,1],f32>
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%0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32>
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return %0 : !torch.vtensor<[3,2,1],f32>
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}
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// -----
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// CHECK-LABEL: func.func @test_reduce_log_sum_exp_keep_dims_int_input_example
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func.func @test_reduce_log_sum_exp_keep_dims_int_input_example(%arg0: !torch.vtensor<[3,2,2],si64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
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// CHECK: %[[INT7:.+]] = torch.constant.int 7
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// CHECK: %[[NONE:.+]] = torch.constant.none
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// CHECK: %[[FALSE:.+]] = torch.constant.bool false
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// CHECK: %[[CAST:.+]] = torch.aten.to.dtype %arg0, %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,2],si64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,2],si64>
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// CHECK: %[[EXP:.+]] = torch.aten.exp %[[CAST]] : !torch.vtensor<[3,2,2],si64> -> !torch.vtensor<[3,2,2],si64>
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// CHECK: %[[DIMS:.+]] = torch.prim.ListConstruct : () -> !torch.list<int>
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// CHECK: %[[TRUE:.+]] = torch.constant.bool true
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// CHECK: %[[SUM:.+]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIMS]], %[[TRUE]], %[[NONE]] : !torch.vtensor<[3,2,2],si64>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[3,2,1],f32>
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// CHECK: %[[LOG:.+]] = torch.aten.log1p %[[SUM]] : !torch.vtensor<[3,2,1],f32> -> !torch.vtensor<[3,2,1],f32>
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// CHECK: %[[CASTLIKE:.+]] = torch.aten.to.dtype %[[LOG]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[3,2,1],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[3,2,1],f32>
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// CHECK: return %[[CASTLIKE]] : !torch.vtensor<[3,2,1],f32>
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%0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32>
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return %0 : !torch.vtensor<[3,2,1],f32>
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}
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// -----
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// CHECK-LABEL: @test_reduce_mean_negative_axes_keepdims_example
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func.func @test_reduce_mean_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64} {
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// CHECK: %[[TENSOR:.+]] = torch.vtensor.literal(dense<-2> : tensor<1xsi64>) : !torch.vtensor<[1],si64>

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